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Current Research and Scholarly Interests

(1) Imaging of radionuclides with single-cell resolution: Currently, radionuclide tracer imaging is the most sensitive assay for probing subtle biochemical processes in living subjects. Molecular imaging with PET and SPECT has become crucial both for basic science research and for patient management. However, little is known about how those radionuclide tracers interact with cell at the single cell level. I am currently developing a new imaging tool call the radioluminescence microscope that can image these tracers in a standard microscopy environment. This new tool allows researchers at Stanford to visualize how radionuclide tracers distribute in a living cell population.

(2) X-ray molecular imaging: Molecular imaging offers the ability to probe subtle biological signals that are characteristic of disease onset and progression. It can also monitor the response of a disease to treatment before any anatomical changes occur. My research explores two emerging imaging techniques that can probe multiple disease biomarkers in a non-invasive fashion. In both imaging techniques, a contrast agent is introduced that can produce a distinguishable signal when irradiated with X-ray. This feature makes it possible to obtain molecular information during a CT examination. The two imaging techniques differ in the following: In X-ray luminescence imaging, the contrast agent is a radioluminescent nanoparticle that produces near-infrared light under X-ray irradiation. In X-ray fluorescence imaging, the contrast agent is a high-atomic-number element that emits a characteristic X-ray signal under irradiation.

(3) High-performance medical computing: Efficient computing now requires using multi- and many-core processors--which embed multiple computing elements in a single chip. New medical imaging algorithms must be designed that are aware of the parallel computing capabilities of new computer hardware. In my work, I develop medical imaging algorithms adapted to these new parallel architectures. Clinically, those algorithms can shorten the time required to process data by as much as tenfold, removing a critical bottleneck in the clinical workflow. One of the most promising platform for medical computing is the graphics processing unit: originally a gadget sought by serious computer gamers, it is now used as an inexpensive supercomputer on-a-chip by researchers in all fields.

Publications

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Abstract

Low-light microscopy methods are receiving increased attention as new applications have emerged. One such application is to allow longitudinal imaging of light-sensitive cells with no phototoxicity and no photobleaching of fluorescent biomarkers. Another application is for imaging signals that are inherently dim and undetectable using standard microscopy techniques, such as bioluminescence, chemiluminescence or radioluminescence. In this protocol, we provide instructions on how to build a modular low-light microscope (1-4 d) by coupling two microscope objective lenses, back to back from each other, using standard optomechanical components. We also provide directions on how to image dim signals such as those of radioluminescence (1-1.5 h), bioluminescence (∼30 min) and low-excitation fluorescence (∼15 min). In particular, radioluminescence microscopy is explained in detail, as it is a newly developed technique that enables the study of small-molecule transport (e.g., radiolabeled drugs, metabolic precursors and nuclear medicine contrast agents) by single cells without perturbing endogenous biochemical processes. In this imaging technique, a scintillator crystal (e.g., CdWO4) is placed in close proximity to the radiolabeled cells, where it converts the radioactive decays into optical flashes detectable using a sensitive camera. Using the image reconstruction toolkit provided in this protocol, the flashes can be reconstructed to yield high-resolution images of the radiotracer distribution. With appropriate timing, the three aforementioned imaging modalities may be performed together on a population of live cells, allowing the user to perform parallel functional studies of cell heterogeneity at the single-cell level.

Abstract

Radioluminescence microscopy can visualize the distribution of beta-emitting radiotracers in live single cells with high resolution. Here, we perform a computational simulation of (18) F positron imaging using this modality to better understand how radioluminescence signals are formed and to assist in optimizing the experimental setup and image processing.First, the transport of charged particles through the cell and scintillator and the resulting scintillation is modeled using the GEANT4 Monte-Carlo simulation. Then, the propagation of the scintillation light through the microscope is modeled by a convolution with a depth-dependent point-spread function, which models the microscope response. Finally, the physical measurement of the scintillation light using an electron-multiplying charge-coupled device (EMCCD) camera is modeled using a stochastic numerical photosensor model, which accounts for various sources of noise. The simulated output of the EMCCD camera is further processed using our ORBIT image reconstruction methodology to evaluate the endpoint images.The EMCCD camera model was validated against experimentally acquired images and the simulated noise, as measured by the standard deviation of a blank image, was found to be accurate within 2% of the actual detection. Furthermore, point source simulations found that a reconstructed spatial resolution of 18.5 μm can be achieved near the scintillator. As the source is moved away from the scintillator, spatial resolution degrades at a rate of 3.5 μm per μm distance. These results agree well with the experimentally measured spatial resolution of 30-40 μm (live cells). The simulation also shows that the system sensitivity is 26.5%, which is also consistent with our previous experiments. Finally, an image of a simulated sparse set of single cells is visually similar to the measured cell image.Our simulation methodology agrees with experimental measurements taken with radioluminescence microscopy. This in silico approach can be used to guide further instrumentation developments and to provide a framework for improving image reconstruction.

Abstract

Flexible radioluminescence imaging (Flex-RLI) is an optical method for imaging (18)F-fluorodeoxyglucose (FDG)-avid tumors. The authors hypothesize that a gadolinium oxysulfide: terbium (GOS:Tb) flexible scintillator, which loosely conforms to the body contour, can enhance tumor signal-to-background ratio (SBR) compared with RLI, which utilizes a flat scintillator. The purpose of this paper is to characterize flex-RLI with respect to alternative modalities including RLI, beta-RLI (RLI with gamma rejection), and Cerenkov luminescence imaging (CLI).The photon sensitivity, spatial resolution, and signal linearity of flex-RLI were characterized with in vitro phantoms. In vivo experiments utilizing 13 nude mice inoculated with the head and neck (UMSCC1-Luc) cell line were then conducted in accordance with the institutional Administrative Panel on Laboratory Animal Care. After intravenous injection of (18)F-FDG, the tumor SBR values for flex-RLI were compared to those for RLI, beta-RLI, and CLI using the Wilcoxon signed rank test.With respect to photon sensitivity, RLI, beta-RLI, and flex-RLI produced 1216.2, 407.0, and 98.6 times more radiance per second than CLI. Respective full-width half maximum values across a 0.5 mm capillary tube were 6.9, 6.4, 2.2, and 1.5 mm, respectively. Flex-RLI demonstrated a near perfect correlation with (18)F activity (r = 0.99). Signal uniformity for flex-RLI improved after more aggressive homogenization of the GOS powder with the silicone elastomer during formulation. In vivo, the SBR value for flex-RLI (median 1.29; interquartile range 1.18-1.36) was statistically greater than that for RLI (1.08; 1.02-1.14; p < 0.01) by 26%. However, there was no statistically significant difference in SBR values between flex-RLI and beta-RLI (p = 0.92). Furthermore, there was no statistically significant difference in SBR values between flex-RLI and CLI (p = 0.11) in a more limited dataset.Flex-RLI provides high quality images with SBRs comparable to those from CLI and beta-RLI in a single 10 s acquisition.

Abstract

The radiotracer 3'-deoxy-3'-(18)F-fluorothymidine ((18)F-FLT) is commonly used to measure cell proliferation in vivo. As a marker of cell proliferation, (18)F-FLT is expected to be differentially taken up by arrested and actively dividing cells, but PET measures only aggregate uptake by tumor cells and therefore the single-cell distribution of (18)F-FLT is unknown. We used a novel in vitro radioluminescence microscopy technique to measure the differential distribution of (18)F-FLT radiotracer with single-cell precision.Using radioluminescence microscopy, we imaged the absolute uptake of (18)F-FLT in live MDA-MB-231 cells grown under different serum conditions. We then compared (18)F-FLT uptake with a standard measure of cell proliferation, using fluorescence microscopy of 5-ethynyl-2'-deoxyuridine incorporation in fixed cells.According to 5-ethynyl-2'-deoxyuridine staining, few cells (1%) actively cycled under serum deprivation whereas most of them (71%) did under 20% serum. The distribution of (18)F-FLT reflected this dynamic. At 0% serum, uptake of (18)F-FLT was heterogeneous but relatively low. At 20% serum, a subpopulation of (18)F-FLT-avid cells, representing 61% of the total population, emerged. Uptake of (18)F-FLT in this population was 5-fold higher than in the remainder of the cells. Such a dichotomous distribution is not typically observed with other radiotracers, such as (18)F-FDG.These results suggest that increased (18)F-FLT uptake by proliferating cells is due to a greater fraction of (18)F-FLT-avid cells rather than a change in (18)F-FLT uptake by individual cells. This finding is consistent with the fact that (18)F-FLT uptake is mediated by thymidine kinase 1 expression, which is higher in actively dividing cells. Overall, these findings suggest that, within the same patient, changes in (18)F-FLT uptake reflect changes in the number of actively dividing cells, provided other parameters remain the same.

Abstract

A recent method based on positron emission was reported for tracking moving point sources using the Inveon PET system. However, the effect of scanner background noise was not further explored. Here, we evaluate tracking with the Genisys4, a bismuth germanate-based PET system, which has no significant intrinsic background and may be better suited to tracking lower and/or faster activity sources. Position-dependent sensitivity of the Genisys4 was simulated in Geant4 Application for Tomographic Emission (GATE) using a static (18)F point source. Trajectories of helically moving point sources with varying activity and rotation speed were reconstructed from list-mode data as described previously. Simulations showed that the Inveon's ability to track sources within 2 mm of localization error is limited to objects with a velocity-to-activity ratio < 0.13 mm/decay, compared to < 0.29 mm/decay for the Genisys4. Tracking with the Genisys4 was then validated using a physical phantom of helically moving [(18)F] fluorodeoxyglucose-in-oil droplets (< 0.24 mm diameter, 139-296 Bq), yielding < 1 mm localization error under the tested conditions, with good agreement between simulated sensitivity and measured activity (Pearson correlation R = .64, P < .05 in a representative example). We have investigated the tracking performance with the Genisys4, and results suggest the feasibility of tracking low activity, point source-like objects with this system.

Abstract

Cancer cells release high levels of lactate that has been correlated to increased metastasis and tumor recurrence. Single-cell measurements of lactate release can identify malignant cells and help decipher metabolic cancer pathways. We present here a novel droplet microfluidic method that allows the fast and quantitative determination of lactate release in many single cells. Using passive forces, droplets encapsulated cells are positioned in an array. The single-cell lactate release rate is determined from the increase in droplet fluorescence as the lactate is enzymatically converted to a fluorescent product. The method is used to measure the cell-to-cell variance of lactate release in K562 leukemia and U87 glioblastoma cancer cell lines and under the chemical inhibition of lactate efflux. The technique can be used in the study of cancer biology, but more broadly in cell biology, to capture the full range of stochastic variations in glycolysis activity in heterogeneous cell populations in a repeatable and high-throughput manner.

Abstract

Complete removal of residual tumor tissue during surgical resection improves patient outcomes. However, it is often difficult for surgeons to delineate the tumor beyond its visible boundary. This has led to the development of intraoperative detectors that can image radiotracers accumulated within tumors, thus facilitating the removal of residual tumor tissue during surgical procedures. We introduce a beta imaging system that converts the beta radiation from the radiotracer into photons close to the decay origin through a CdWO4 scintillator and does not use any optical elements. The signal is relayed onto an EMCCD chip through a wound imaging fiber. The sensitivity of the device allows imaging of activity down to 100 nCi and the system has a resolution of at least 500 μm with a field of view of 4.80 × 6.51 mm. Advances in handheld beta cameras have focused on hardware improvements, but we apply machine vision to the recorded images to extract more information. We automatically classify sample regions in human renal cancer tissue ex-vivo into tumor or benign tissue based on image features. Machine vision boosts the ability of our system to distinguish tumor from healthy tissue by a factor of 9 ± 3 and can be applied to other beta imaging probes.

Abstract

Cerenkov luminescence imaging (CLI) can provide high-resolution images of (18)F-FDG-avid tumors but requires prolonged acquisition times because of low photon sensitivity. In this study, we proposed a new modality, termed β-radioluminescence imaging (β-RLI), which incorporates a scintillator with a γ-rejection strategy for imaging β particles. We performed a comparative evaluation of β-RLI with CLI in both in vitro and in vivo systems.Using in vitro phantoms, we characterized the photon sensitivity and resolution of CLI and β-RLI. We also conducted a series of in vivo experiments with xenograft mouse models using both amelanotic (A375, UMSCC1-Luc) and melanotic (B16F10-Luc) cell lines. The B16F10 and UMSCC1 cell lines were transfected with the luciferase gene (Luc). CLI was acquired over 300 s, and β-RLI was acquired using two 10-s acquisitions. We correlated (18)F -: FDG activities, as assessed by PET, with tumor radiances for both β-RLI and CLI. We also compared tumor signal-to-background ratios (SBRs) between these modalities for amelanotic and melanotic tumors.For in vitro experiments, the photon sensitivity for β-RLI was 560-fold greater than that for CLI. However, the spatial resolution for β-RLI (4.4 mm) was inferior to that of CLI (1.0 mm). For in vivo experiments, correlations between (18)F-FDG activity and tumor radiance were 0.52 (P < 0.01) for β-RLI, 0.81 (P = 0.01) for amelanotic lesions with CLI, and -0.08 (negative contrast; P = 0.80) for melanotic lesions with CLI. Nine of 13 melanotic lesions had an SBR less than 1 for CLI, despite an SBR greater than 1 among all lesions for β-RLI.β-RLI can produce functional images of both amelanotic and melanotic tumors in a shorter time frame than CLI. Further engineering developments are needed to realize the full clinical potential of this modality.

Abstract

Beta-emitting isotopes Fluorine-18 and Yttrium-90 are tested for their potential to stimulate gold nanoclusters conjugated with blood serum proteins (AuNCs). AuNCs excited by either medical radioisotope are found to be highly effective ionizing radiation energy transfer mediators, suitable for in vivo optical imaging. AuNCs synthesized with protein templates convert beta-decaying radioisotope energy into tissue-penetrating optical signals between 620 and 800 nm. Optical signals are not detected from AuNCs incubated with Technetium-99m, a pure gamma emitter that is used as a control. Optical emission from AuNCs is not proportional to Cerenkov radiation, indicating that the energy transfer between the radionuclide and AuNC is only partially mediated by Cerenkov photons. A direct Coulombic interaction is proposed as a novel and significant mechanism of energy transfer between decaying radionuclides and AuNCs.

Abstract

Radiolabels can be used to detect small biomolecules with high sensitivity and specificity without interfering with the biochemical activity of the labeled molecule. For instance, the radiolabeled glucose analogue, [18F]fluorodeoxyglucose (FDG), is routinely used in positron emission tomography (PET) scans for cancer diagnosis, staging, and monitoring. However, despite their widespread usage, conventional radionuclide techniques are unable to measure the variability and modulation of FDG uptake in single cells. We present here a novel microfluidic technique, dubbed droplet radiofluidics, that can measure radiotracer uptake for single cells encapsulated into an array of microdroplets. The advantages of this approach are multiple. First, droplets can be quickly and easily positioned in a predetermined pattern for optimal imaging throughput. Second, droplet encapsulation reduces cell efflux as a confounding factor, because any effluxed radionuclide is trapped in the droplet. Last, multiplexed measurements can be performed using fluorescent labels. In this new approach, intracellular radiotracers are imaged on a conventional fluorescence microscope by capturing individual flashes of visible light that are produced as individual positrons, emitted during radioactive decay, traverse a scintillator plate placed below the cells. This method is used to measure the cell-to-cell heterogeneity in the uptake of tracers such as FDG in cell lines and cultured primary cells. The capacity of the platform to perform multiplexed measurements was demonstrated by measuring differential FDG uptake in single cells subjected to different incubation conditions and expressing different types of glucose transporters. This method opens many new avenues of research in basic cell biology and human disease by capturing the full range of stochastic variations in highly heterogeneous cell populations in a repeatable and high-throughput manner.

Abstract

Virtually all biomedical applications of positron emission tomography (PET) use images to represent the distribution of a radiotracer. However, PET is increasingly used in cell tracking applications, for which the "imaging" paradigm may not be optimal. Here, we investigate an alternative approach, which consists in reconstructing the time-varying position of individual radiolabeled cells directly from PET measurements. As a proof of concept, we formulate a new algorithm for reconstructing the trajectory of one single moving cell directly from list-mode PET data. We model the trajectory as a 3-D B-spline function of the temporal variable and use nonlinear optimization to minimize the mean-square distance between the trajectory and the recorded list-mode coincidence events. Using Monte Carlo simulations (GATE), we show that this new algorithm can track a single source moving within a small-animal PET system with 3 mm accuracy provided that the activity of the cell [Bq] is greater than four times its velocity [mm/s]. The algorithm outperforms conventional ML-EM as well as the "minimum distance" method used for positron emission particle tracking (PEPT). The new method was also successfully validated using experimentally acquired PET data. In conclusion, we demonstrated the feasibility of a new method for tracking a single moving cell directly from PET list-mode data, at the whole-body level, for physiologically relevant activities and velocities.

Abstract

Shortwave infrared (SWIR or NIR-II) light provides significant advantages for imaging biological structures due to reduced autofluorescence and photon scattering. Here, we report on the development of rare-earth nanoprobes that exhibit SWIR luminescence following X-ray irradiation. We demonstrate the ability of X-ray-induced SWIR luminescence (X-IR) to monitor biodistribution and map lymphatic drainage. Our results indicate X-IR imaging is a promising new modality for preclinical applications and has potential for dual-modality molecular disease imaging.

Abstract

Preoperative lymphoscintigraphy (PLS) combined with intraoperative gamma probe (GP) localization is standard procedure for localizing the sentinel lymph nodes (SLN) in melanoma and breast cancer. In this study, we evaluated the ability of a novel intraoperative handheld gamma camera (IHGC) to image SLNs during surgery.The IHGC is a small-field-of-view camera optimized for real-time imaging of lymphatic drainage patterns. Unlike conventional cameras, the IHGC can acquire useful images in a few seconds in a free-running fashion and be moved manually around the patient to find a suitable view of the node. Thirty-nine melanoma and eleven breast cancer patients underwent a modified SLN biopsy protocol in which nodes localized with the GP were imaged with the IHGC. The IHGC was also used to localize additional nodes that could not be found with the GP.The removal of 104 radioactive SLNs was confirmed ex vivo by GP counting. In vivo, the relative node detection sensitivity was 88.5 (82.3, 94.6)% for the IHGC (used in conjunction with the GP) and 94.2 (89.7, 98.7)% for the GP alone, a difference not found to be statistically significant (McNemar test, p = 0.24).Small radioactive SLNs can be visualized intraoperatively using the IHGC with exposure time of 20 s or less, with no significant difference in node detection sensitivity compared to a GP. The IHGC is a useful complement to the GP, especially for SLNs that are difficult to locate with the GP alone.

Abstract

X-ray fluorescence computed tomography (XFCT) imaging has been focused on the detection of K-shell x-rays. The potential utility of L-shell x-ray XFCT is, however, not well studied. Here we report the first Monte Carlo (MC) simulation of preclinical L-shell XFCT imaging of Cisplatin. We built MC models for both L- and K-shell XFCT with different excitation energies (15 and 30 keV for L-shell and 80 keV for K-shell XFCT). Two small-animal sized imaging phantoms of 2 and 4 cm diameter containing a series of objects of 0.6 to 2.7 mm in diameter at 0.7 to 16 mm depths with 10 to 250 µg mL(-1) concentrations of Pt are used in the study. Transmitted and scattered x-rays were collected with photon-integrating transmission detector and photon-counting detector arc, respectively. Collected data were rearranged into XFCT and transmission CT sinograms for image reconstruction. XFCT images were reconstructed with filtered back-projection and with iterative maximum-likelihood expectation maximization without and with attenuation correction. While K-shell XFCT was capable of providing an accurate measurement of Cisplatin concentration, its sensitivity was 4.4 and 3.0 times lower than that of L-shell XFCT with 15 keV excitation beam for the 2 cm and 4 cm diameter phantom, respectively. With the inclusion of excitation and fluorescence beam attenuation correction, we found that L-shell XFCT was capable of providing fairly accurate information of Cisplatin concentration distribution. With a dose of 29 and 58 mGy, clinically relevant Cisplatin Pt concentrations of 10 µg mg(-1) could be imaged with L-shell XFCT inside a 2 cm and 4 cm diameter object, respectively.

Abstract

Purpose: To assess whether air scintillation produced during standard radiation treatments can be visualized and used to monitor a beam in a nonperturbing manner.Methods: Air scintillation is caused by the excitation of nitrogen gas by ionizing radiation. This weak emission occurs predominantly in the 300-430 nm range. An electron-multiplication charge-coupled device camera, outfitted with an f∕0.95 lens, was used to capture air scintillation produced by kilovoltage photon beams and megavoltage electron beams used in radiation therapy. The treatment rooms were prepared to block background light and a short-pass filter was utilized to block light above 440 nm.Results: Air scintillation from an orthovoltage unit (50 kVp, 30 mA) was visualized with a relatively short exposure time (10 s) and showed an inverse falloff (r(2) = 0.89). Electron beams were also imaged. For a fixed exposure time (100 s), air scintillation was proportional to dose rate (r(2) = 0.9998). As energy increased, the divergence of the electron beam decreased and the penumbra improved. By irradiating a transparent phantom, the authors also showed that Cherenkov luminescence did not interfere with the detection of air scintillation. In a final illustration of the capabilities of this new technique, the authors visualized air scintillation produced during a total skin irradiation treatment.Conclusions: Air scintillation can be measured to monitor a radiation beam in an inexpensive and nonperturbing manner. This physical phenomenon could be useful for dosimetry of therapeutic radiation beams or for online detection of gross errors during fractionated treatments.

Abstract

Here, we demonstrate that biomolecule-directed metal clusters are applicable in the study of hard X-ray excited optical luminescence, promising a new direction in the development of novel X-ray-activated imaging probes.

Abstract

Radioluminescence microscopy is a new method for imaging radionuclide uptake by single live cells with a fluorescence microscope. Here, we report a particle-counting scheme that improves spatial resolution by overcoming the β-range limit.Short frames (10 μs-1 s) were acquired using a high-gain camera coupled to a microscope to capture individual ionization tracks. Optical reconstruction of the β-ionization track (ORBIT) was performed to localize individual β decays, which were aggregated into a composite image. The new approach was evaluated by imaging the uptake of (18)F-FDG in nonconfluent breast cancer cells.After image reconstruction, ORBIT resulted in better definition of individual cells. This effect was particularly noticeable in small clusters (2-4 cells), which occur naturally even for nonconfluent cell cultures. The annihilation and Bremsstrahlung photon background signal was markedly lower. Single-cell measurements of (18)F-FDG uptake that were computed from ORBIT images more closely matched the uptake of the fluorescent glucose analog (Pearson correlation coefficient, 0.54 vs. 0.44, respectively).ORBIT can image the uptake of a radiotracer in living cells with spatial resolution better than the β range. In principle, ORBIT may also allow for greater quantitative accuracy because the decay rate is measured more directly, with no dependency on the β-particle energy.

Abstract

In this study, cyclometalated iridium(III) complex-doped polymer dots were synthesized and shown to emit luminescence upon X-ray irradiation, potentially serving as a new probe for molecular imaging during X-ray computed tomography.

Abstract

The processing speed for positron emission tomography (PET) image reconstruction has been greatly improved in recent years by simply dividing the workload to multiple processors of a graphics processing unit (GPU). However, if this strategy is generalized to a multi-GPU cluster, the processing speed does not improve linearly with the number of GPUs. This is because large data transfer is required between the GPUs after each iteration, effectively reducing the parallelism. This paper proposes a novel approach to reformulate the maximum likelihood expectation maximization (MLEM) algorithm so that it can scale up to many GPU nodes with less frequent inter-node communication. While being mathematically different, the new algorithm maximizes the same convex likelihood function as MLEM, thus converges to the same solution. Experiments on a multi-GPU cluster demonstrate the effectiveness of the proposed approach.

Abstract

Developing an imaging method to directly monitor the spatial distribution of platinum-based (Pt) drugs at the tumor region is of critical importance for early assessment of treatment efficacy and personalized treatment. In this study, the authors investigated the feasibility of imaging platinum (Pt)-based drug distribution using x-ray fluorescence (XRF, a.k.a. characteristic x ray) CT (XFCT).A 5-mm-diameter pencil beam produced by a polychromatic x-ray source equipped with a tungsten anode was used to stimulate emission of XRF photons from Pt drug embedded within a water phantom. The phantom was translated and rotated relative to the stationary pencil beam in a first-generation CT geometry. The x-ray energy spectrum was collected for 18 s at each position using a cadmium telluride detector. The spectra were then used for the K-shell XRF peak isolation and sinogram generation for Pt. The distribution and concentration of Pt were reconstructed with an iterative maximum likelihood expectation maximization algorithm. The capability of XFCT to multiplexed imaging of Pt, gadolinium (Gd), and iodine (I) within a water phantom was also investigated.Measured XRF spectrum showed a sharp peak characteristic of Pt with a narrow full-width at half-maximum (FWHM) (FWHMKα1 = 1.138 keV, FWHMKα2 = 1.052 keV). The distribution of Pt drug in the water phantom was clearly identifiable on the reconstructed XRF images. Our results showed a linear relationship between the XRF intensity of Pt and its concentrations (R(2) = 0.995), suggesting that XFCT is capable of quantitative imaging. A transmission CT image was also obtained to show the potential of the approach for providing attenuation correction and morphological information. Finally, the distribution of Pt, Gd, and I in the water phantom was clearly identifiable in the reconstructed images from XFCT multiplexed imaging.XFCT is a promising modality for monitoring the spatial distribution of Pt drugs. The technique may be useful in tailoring tumor treatment regimen in the future.

Abstract

Simultaneous imaging of multiple probes or biomarkers represents a critical step toward high specificity molecular imaging. In this work, we propose to utilize the element-specific nature of the X-ray fluorescence (XRF) signal for imaging multiple elements simultaneously (multiplexing) using XRF computed tomography (XFCT). A 5-mm-diameter pencil beam produced by a polychromatic X-ray source (150 kV, 20 mA) was used to stimulate emission of XRF photons from 2% (weight/volume) gold (Au), gadolinium (Gd), and barium (Ba) embedded within a water phantom. The phantom was translated and rotated relative to the stationary pencil beam in a first-generation CT geometry. The X-ray energy spectrum was collected for 18 s at each position using a cadmium telluride detector. The spectra were then used to isolate the K shell XRF peak and to generate sinograms for the three elements of interest. The distribution and concentration of the three elements were reconstructed with the iterative maximum likelihood expectation maximization algorithm. The linearity between the XFCT intensity and the concentrations of elements of interest was investigated. We found that measured XRF spectra showed sharp peaks characteristic of Au, Gd, and Ba. The narrow full-width at half-maximum (FWHM) of the peaks strongly supports the potential of XFCT for multiplexed imaging of Au, Gd, and Ba ( FWHM(Au,Kα1) = 0.619 keV, FWHM(Au,Kα2)=1.371 keV , FWHM(Gd,Kα)=1.297 keV, FWHM(Gd,Kβ)=0.974 keV , FWHM(Ba,Kα)=0.852 keV, and FWHM(Ba,Kβ)=0.594 keV ). The distribution of Au, Gd, and Ba in the water phantom was clearly identifiable in the reconstructed XRF images. Our results showed linear relationships between the XRF intensity of each tested element and their concentrations ( R(2)(Au)=0.944 , R(Gd)(2)=0.986, and R(Ba)(2)=0.999), suggesting that XFCT is capable of quantitative imaging. Finally, a transmission CT image was obtained to show the potential of the approach for providing attenuation correction and morphological information. In conclusion, XFCT is a promising modality for multiplexed imaging of high atomic number probes.

Abstract

The feasibility of medical imaging using a medical linear accelerator to generate acoustic waves is investigated. This modality, x-ray acoustic computed tomography (XACT), has the potential to enable deeper tissue penetration in tissue than photoacoustic tomography via laser excitation.Short pulsed (μs-range) 10 MV x-ray beams with dose-rate of approximately 30 Gy∕min were generated from a medical linear accelerator. The acoustic signals were collected with an ultrasound transducer (500 KHz central frequency) positioned around an object. The transducer, driven by a computer-controlled step motor to scan around the object, detected the resulting acoustic signals in the imaging plane at each scanning position. A pulse preamplifier, with a bandwidth of 20 KHz-2 MHz at -3 dB, and switchable gains of 40 and 60 dB, received the signals from the transducer and delivered the amplified signals to a secondary amplifier. The secondary amplifier had bandwidth of 20 KHz-30 MHz at -3 dB, and a gain range of 10-60 dB. Signals were recorded and averaged 128 times by an oscilloscope. A sampling rate of 100 MHz was used to record 2500 data points at each view angle. One set of data incorporated 200 positions as the receiver moved 360°. The x-ray generated acoustic image was then reconstructed with the filtered back projection algorithm.The x-ray generated acoustic signals were detected from a lead rod embedded in a chicken breast tissue. The authors found that the acoustic signal was proportional to the x-ray dose deposition, with a correlation of 0.998. The two-dimensional XACT images of the lead rod embedded in chicken breast tissue were found to be in good agreement with the shape of the object.The first x-ray acoustic computed tomography image is presented. The new modality may be useful for a number of applications, such as providing the location of a fiducial, or monitoring x-ray dose distribution during radiation therapy. Although much work is needed to improve the image quality of XACT and to explore its performance in other irradiation energies, the benefits of this modality, as highlighted in this work, encourage further study.

Abstract

Radiotracers play an important role in interrogating molecular processes both in vitro and in vivo. However, current methods are limited to measuring average radiotracer uptake in large cell populations and, as a result, lack the ability to quantify cell-to-cell variations. Here we apply a new technique, termed radioluminescence microscopy, to visualize radiotracer uptake in single living cells, in a standard fluorescence microscopy environment. In this technique, live cells are cultured sparsely on a thin scintillator plate and incubated with a radiotracer. Light produced following beta decay is measured using a highly sensitive microscope. Radioluminescence microscopy revealed strong heterogeneity in the uptake of [(18)F]fluoro-deoxyglucose (FDG) in single cells, which was found consistent with fluorescence imaging of a glucose analog. We also verified that dynamic uptake of FDG in single cells followed the standard two-tissue compartmental model. Last, we transfected cells with a fusion PET/fluorescence reporter gene and found that uptake of FHBG (a PET radiotracer for transgene expression) coincided with expression of the fluorescent protein. Together, these results indicate that radioluminescence microscopy can visualize radiotracer uptake with single-cell resolution, which may find a use in the precise characterization of radiotracers.

Abstract

Cerenkov luminescence imaging (CLI) is an emerging new molecular imaging modality that is relatively inexpensive, easy to use, and has high throughput. CLI can image clinically available PET and SPECT probes using optical instrumentation. Cerenkov luminescence endoscopy (CLE) is one of the most intriguing applications that promise potential clinical translation. We developed a prototype customized fiberscopic Cerenkov imaging system to investigate the potential in guiding minimally invasive surgical resection.All experiments were performed in a dark chamber. Cerenkov luminescence from (18)F-FDG samples containing decaying radioactivity was transmitted through an optical fiber bundle and imaged by an intensified charge-coupled device camera. Phantoms filled with (18)F-FDG were used to assess the imaging spatial resolution. Finally, mice bearing subcutaneous C6 glioma cells were injected intravenously with (18)F-FDG to determine the feasibility of in vivo imaging. The tumor tissues were exposed, and CLI was performed on the mouse before and after surgical removal of the tumor using the fiber-based imaging system and compared with a commercial optical imaging system.The sensitivity of this particular setup was approximately 45 kBq (1.21 μCi)/300 μL. The 3 smallest sets of cylindric holes in a commercial SPECT phantom were identifiable via this system, demonstrating that the system has a resolution better than 1.2 mm. Finally, the in vivo tumor imaging study demonstrated the feasibility of using CLI to guide the resection of tumor tissues.This proof-of-concept study explored the feasibility of using fiber-based CLE for the detection of tumor tissue in vivo for guided surgery. With further improvements of the imaging sensitivity and spatial resolution of the current system, CLE may have a significant application in the clinical setting in the near future.

Abstract

This work provides a comprehensive Monte Carlo study of X-ray fluorescence computed tomography (XFCT) and K-edge imaging system, including the system design, the influence of various imaging components, the sensitivity and resolution under various conditions. We modified the widely used EGSnrc/DOSXYZnrc code to simulate XFCT images of two acrylic phantoms loaded with various concentrations of gold nanoparticles and Cisplatin for a number of XFCT geometries. In particular, reconstructed signal as a function of the width of the detector ring, its angular coverage and energy resolution were studied. We found that XFCT imaging sensitivity of the modeled systems consisting of a conventional X-ray tube and a full 2-cm-wide energy-resolving detector ring was 0.061% and 0.042% for gold nanoparticles and Cisplatin, respectively, for a dose of ∼ 10 cGy. Contrast-to-noise ratio (CNR) of XFCT images of the simulated acrylic phantoms was higher than that of transmission K-edge images for contrast concentrations below 0.4%.

Abstract

We demonstrate the ability to image multiple nanoparticle-based contrast agents simultaneously using a nanophosphor platform excited by either radiopharmaceutical or X-ray irradiation. These radioluminescent nanoparticles emit optical light at unique wavelengths depending on their lanthanide dopant, enabling multiplexed imaging. This study demonstrates the separation of two distinct nanophosphor contrast agents in gelatin phantoms with a recovered phosphor separation correlation of -0.98. The ability to distinguish the two nanophosphors and a Cerenkov component is then demonstrated in a small animal phantom. Combined with the high-resolution potential of low-scattering X-ray excitation, this imaging technique may be a promising method to probe molecular processes in living organisms.

Abstract

Four-dimensional CT (4DCT) and cone beam CT (CBCT) are widely used in radiation therapy for accurate tumor target definition and localization. However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed. Efficient use of these imaging techniques in the clinic requires high-performance computing. The purpose of this work is to develop a novel ultrafast, scalable and reliable image reconstruction technique for 4D CBCT∕CT using a parallel computing framework called MapReduce. We show the utility of MapReduce for solving large-scale medical physics problems in a cloud computing environment.In this work, we accelerated the Feldcamp-Davis-Kress (FDK) algorithm by porting it to Hadoop, an open-source MapReduce implementation. Gated phases from a 4DCT scans were reconstructed independently. Following the MapReduce formalism, Map functions were used to filter and backproject subsets of projections, and Reduce function to aggregate those partial backprojection into the whole volume. MapReduce automatically parallelized the reconstruction process on a large cluster of computer nodes. As a validation, reconstruction of a digital phantom and an acquired CatPhan 600 phantom was performed on a commercial cloud computing environment using the proposed 4D CBCT∕CT reconstruction algorithm.Speedup of reconstruction time is found to be roughly linear with the number of nodes employed. For instance, greater than 10 times speedup was achieved using 200 nodes for all cases, compared to the same code executed on a single machine. Without modifying the code, faster reconstruction is readily achievable by allocating more nodes in the cloud computing environment. Root mean square error between the images obtained using MapReduce and a single-threaded reference implementation was on the order of 10(-7). Our study also proved that cloud computing with MapReduce is fault tolerant: the reconstruction completed successfully with identical results even when half of the nodes were manually terminated in the middle of the process.An ultrafast, reliable and scalable 4D CBCT∕CT reconstruction method was developed using the MapReduce framework. Unlike other parallel computing approaches, the parallelization and speedup required little modification of the original reconstruction code. MapReduce provides an efficient and fault tolerant means of solving large-scale computing problems in a cloud computing environment.

Abstract

Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes.

Abstract

List-mode processing is an efficient way of dealing with the sparse nature of positron emission tomography (PET) data sets and is the processing method of choice for time-of-flight (ToF) PET image reconstruction. However, the massive amount of computation involved in forward projection and backprojection limits the application of list-mode reconstruction in practice, and makes it challenging to incorporate accurate system modeling.The authors present a novel formulation for computing line projection operations on graphics processing units (GPUs) using the compute unified device architecture (CUDA) framework, and apply the formulation to list-mode ordered-subsets expectation maximization (OSEM) image reconstruction. Our method overcomes well-known GPU challenges such as divergence of compute threads, limited bandwidth of global memory, and limited size of shared memory, while exploiting GPU capabilities such as fast access to shared memory and efficient linear interpolation of texture memory. Execution time comparison and image quality analysis of the GPU-CUDA method and the central processing unit (CPU) method are performed on several data sets acquired on a preclinical scanner and a clinical ToF scanner.When applied to line projection operations for non-ToF list-mode PET, this new GPU-CUDA method is >200 times faster than a single-threaded reference CPU implementation. For ToF reconstruction, we exploit a ToF-specific optimization to improve the efficiency of our parallel processing method, resulting in GPU reconstruction >300 times faster than the CPU counterpart. For a typical whole-body scan with 75 × 75 × 26 image matrix, 40.7 million LORs, 33 subsets, and 3 iterations, the overall processing time is 7.7 s for GPU and 42 min for a single-threaded CPU. Image quality and accuracy are preserved for multiple imaging configurations and reconstruction parameters, with normalized root mean squared (RMS) deviation less than 1% between CPU and GPU-generated images for all cases.A list-mode ToF OSEM library was developed on the GPU-CUDA platform. Our studies show that the GPU reformulation is considerably faster than a single-threaded reference CPU method especially for ToF processing, while producing virtually identical images. This new method can be easily adapted to enable more advanced algorithms for high resolution PET reconstruction based on additional information such as depth of interaction (DoI), photon energy, and point spread functions (PSFs).

Abstract

To investigate the feasibility of artificial neural networks (ANN) to reconstruct dose maps for intensity modulated radiation treatment (IMRT) fields compared with those of the treatment planning system (TPS).An artificial feed forward neural network and the back-propagation learning algorithm have been used to replicate dose calculations of IMRT fields obtained from PINNACLE(3) v9.0. The ANN was trained with fluence and dose maps of IMRT fields for 6 MV x-rays, which were obtained from the amorphous silicon (a-Si) electronic portal imaging device of Novalis TX. Those fluence distributions were imported to the TPS and the dose maps were calculated on the horizontal midpoint plane of a water equivalent homogeneous cylindrical virtual phantom. Each exported 2D dose distribution from the TPS was classified into two clusters of high and low dose regions, respectively, based on the K-means algorithm and the Euclidian metric in the fluence-dose domain. The data of each cluster were divided into two sets for the training and validation phase of the ANN, respectively. After the completion of the ANN training phase, 2D dose maps were reconstructed by the ANN and isodose distributions were created. The dose maps reconstructed by ANN were evaluated and compared with the TPS, where the mean absolute deviation of the dose and the γ-index were used.A good agreement between the doses calculated from the TPS and the trained ANN was achieved. In particular, an average relative dosimetric difference of 4.6% and an average γ-index passing rate of 93% were obtained for low dose regions, and a dosimetric difference of 2.3% and an average γ-index passing rate of 97% for high dose region.An artificial neural network has been developed to convert fluence maps to corresponding dose maps. The feasibility and potential of an artificial neural network to replicate complex convolution kernels in the TPS for IMRT dose calculations have been demonstrated.

Abstract

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

Abstract

Positron emission tomography systems are best described by a linear shift-varying model. However, image reconstruction often assumes simplified shift-invariant models to the detriment of image quality and quantitative accuracy. We investigated a shift-varying model of the geometrical system response based on an analytical formulation. The model was incorporated within a list-mode, fully 3D iterative reconstruction process in which the system response coefficients are calculated online on a graphics processing unit (GPU). The implementation requires less than 512 Mb of GPU memory and can process two million events per minute (forward and backprojection). For small detector volume elements, the analytical model compared well to reference calculations. Images reconstructed with the shift-varying model achieved higher quality and quantitative accuracy than those that used a simpler shift-invariant model. For an 8 mm sphere in a warm background, the contrast recovery was 95.8% for the shift-varying model versus 85.9% for the shift-invariant model. In addition, the spatial resolution was more uniform across the field-of-view: for an array of 1.75 mm hot spheres in air, the variation in reconstructed sphere size was 0.5 mm RMS for the shift-invariant model, compared to 0.07 mm RMS for the shift-varying model.

Abstract

X-ray luminescence tomography (XLT) has recently been proposed as a new imaging modality for biological imaging applications. This modality utilizes phosphor nanoparticles which luminesce near-infrared light when excited by x-ray photons. The advantages of this modality are that it uniquely combines the high sensitivity of radioluminescent nanoparticles and the high spatial localization of collimated x-ray beams. Currently, XLT has been demonstrated using x-ray spatial encoding to resolve the imaging volume. However, there are applications where the x-ray excitation may be limited by geometry, where increased temporal resolution is desired, or where a lower dose is mandatory. This paper extends the utility of XLT to meet these requirements by incorporating a photon propagation model into the reconstruction algorithm in an x-ray limited-angle (LA) geometry. This enables such applications as image-guided surgery, where the ability to resolve lesions at depths of several centimeters can be the key to successful resection. The hybrid x-ray/diffuse optical model is first formulated and then demonstrated in a breast-sized phantom, simulating a breast lumpectomy geometry. Both numerical and experimental phantoms are tested, with lesion-simulating objects of various sizes and depths. Results show localization accuracy with median error of 2.2 mm, or 4% of object depth, for small 2-14 mm diameter lesions positioned from 1 to 4.5 cm in depth. This compares favorably with fluorescence optical imaging, which is not able to resolve such small objects at this depth. The recovered lesion size has lower size bias in the x-ray excitation direction than the optical direction, which is expected due to the increased optical scatter. However, the technique is shown to be quite invariant in recovered size with respect to depth, as the standard deviation is less than 2.5 mm. Sensitivity is a function of dose; radiological doses are found to provide sufficient recovery for µg ml(-1) concentrations, while therapy dosages provide recovery for ng ml(-1) concentrations. Experimental phantom results agree closely with the numerical results, with positional errors recovered within 8.6% of the effective depth for a 5 mm object, and within 5.2% of the depth for a 10 mm object. Object-size median error is within 2.3% and 2% for the 5 and 10 mm objects, respectively. For shallow-to-medium depth applications where optical and radio-emission imaging modalities are not ideal, such as in intra-operative procedures, LAXLT may be a useful tool to detect molecular signatures of disease.

Abstract

The graphics processing unit (GPU) has emerged as a competitive platform for computing massively parallel problems. Many computing applications in medical physics can be formulated as data-parallel tasks that exploit the capabilities of the GPU for reducing processing times. The authors review the basic principles of GPU computing as well as the main performance optimization techniques, and survey existing applications in three areas of medical physics, namely image reconstruction, dose calculation and treatment plan optimization, and image processing.

Abstract

We are developing a dual panel breast-dedicated positron emission tomography (PET) system using LSO scintillators coupled to position sensitive avalanche photodiodes (PSAPD). The charge output is amplified and read using NOVA RENA-3 ASICs. This paper shows that the coincidence timing resolution of the RENA-3 ASIC can be improved using certain list-mode calibrations. We treat the calibration problem as a convex optimization problem and use the RENA-3's analog-based timing system to correct the measured data for time dispersion effects from correlated noise, PSAPD signal delays and varying signal amplitudes. The direct solution to the optimization problem involves a matrix inversion that grows order (n(3)) with the number of parameters. An iterative method using single-coordinate descent to approximate the inversion grows order (n). The inversion does not need to run to convergence, since any gains at high iteration number will be low compared to noise amplification. The system calibration method is demonstrated with measured pulser data as well as with two LSO-PSAPD detectors in electronic coincidence. After applying the algorithm, the 511 keV photopeak paired coincidence time resolution from the LSO-PSAPD detectors under study improved by 57%, from the raw value of 16.3 ±0.07 ns full-width at half-maximum (FWHM) to 6.92 ±0.02 ns FWHM ( 11.52 ±0.05 ns to 4.89 ±0.02 ns for unpaired photons).

Abstract

X-ray luminescence computed tomography (XLCT) is proposed as a new molecular imaging modality based on the selective excitation and optical detection of X-ray-excitable phosphor nanoparticles. These nano-sized particles can be fabricated to emit near-infrared (NIR) light when excited with X-rays, and, because because both X-rays and NIR photons propagate long distances in tissue, they are particularly well suited for in vivo biomedical imaging. In XLCT, tomographic images are generated by irradiating the subject using a sequence of programmed X-ray beams, while sensitive photo-detectors measure the light diffusing out of the subject. By restricting the X-ray excitation to a single, narrow beam of radiation, the origin of the optical photons can be inferred regardless of where these photons were detected, and how many times they scattered in tissue. This study presents computer simulations exploring the feasibility of imaging small objects with XLCT, such as research animals. The accumulation of 50 nm phosphor nanoparticles in a 2-mm-diameter target can be detected and quantified with subpicomolar sensitivity using less than 1 cGy of radiation dose. Provided sufficient signal-to-noise ratio, the spatial resolution of the system can be made as high as needed by narrowing the beam aperture. In particular, 1 mm spatial resolution was achieved for a 1-mm-wide X-ray beam. By including an X-ray detector in the system, anatomical imaging is performed simultaneously with molecular imaging via standard X-ray computed tomography (CT). The molecular and anatomical images are spatially and temporally co-registered, and, if a single-pixel X-ray detector is used, they have matching spatial resolution.

Abstract

X-ray luminescence computed tomography (XLCT) is proposed as a new dual molecular/anatomical imaging modality. XLCT is based on the selective excitation and optical detection of x-ray-excitable nanoparticles. As a proof of concept, we built a prototype XLCT system and imaged near-IR-emitting Gd(2)O(2)S:Eu phosphors in various phantoms. Imaging in an optically diffusive medium shows that imaging performance is not affected by optical scatter; furthermore, the linear response of the reconstructed images suggests that XLCT is capable of quantitative imaging.

Abstract

The authors' laboratory is developing a dual-panel, breast-dedicated PET system. The detector panels are built from dual-LSO-position-sensitive avalanche photodiode (PSAPD) modules-units holding two 8 x 8 arrays of 1 mm3 LSO crystals, where each array is coupled to a PSAPD. When stacked to form an imaging volume, these modules are capable of recording the 3-D coordinates of individual interactions of a multiple-interaction photon event (MIPE). The small size of the scintillation crystal elements used increases the likelihood of photon scattering between crystal arrays. In this article, the authors investigate how MIPEs impact the system photon sensitivity, the data acquisition scheme, and the quality and quantitative accuracy of reconstructed PET images.A Monte Carlo simulated PET scan using the dual-panel system was performed on a uniformly radioactive phantom for the photon sensitivity study. To establish the impact of MIPEs on a proposed PSAPD multiplexing scheme, experimental data were collected from a dual-LSO-PSAPD module edge-irradiated with a 22Na point source, the data were compared against simulation data based on an identical setup. To assess the impact of MIPEs on the dual-panel PET images, a simulated PET of a phantom comprising a matrix of hot spherical radiation sources of varying diameters immersed in a warm background was performed. The list-mode output data were used for image reconstruction, where various methods were used for estimating the location of the first photon interaction in MIPEs for more accurate line of response positioning. The contrast recovery coefficient (CRC), contrast to noise ratio (CNR), and the full width at half maximum spatial resolution of the spheres in the reconstructed images were used as figures of merit to facilitate comparison.Compared to image reconstruction employing only events with interactions confined to one LSO array, a potential single photon sensitivity gain of > 46.9% (> 115.7% for coincidence) was noted for a uniform phantom when MIPEs with summed-energy falling within a +/- 12% window around the photopeak were also included. Both experimental and simulation data demonstrate that < 0.4% of the events whose summed-energy deposition falling within that energy window interacted with both crystal arrays within the same dual-LSO-PSAPD module. This result establishes the feasibility of a proposed multiplexed readout of analog output signals of the two PSAPDs within each module. Using MIPEs with summed-energy deposition within the 511 keV +/- 12% photopeak window and a new method for estimating the location of the first photon interaction in MIPEs, the corresponding reconstructed image exhibited a peak CNR of 7.23 for the 8 mm diameter phantom spheres versus a CNR of 6.69 from images based solely on single LSO array interaction events. The improved system photon sensitivity could be exploited to reduce the scan time by up to approximately 10%, while still maintaining image quality comparable to that achieved if MIPEs were excluded.MIPE distribution in the detectors allows the proposed photodetector multiplexing arrangement without significant information loss. Furthermore, acquiring MIPEs can enhance system photon sensitivity and improve PET image CNR and CRC. The system under development can therefore competently acquire and analyze MIPEs and produce high-resolution PET images.

Abstract

The feasibility of x-ray luminescence imaging is investigated using a dual-modality imaging system that merges x-ray and optical imaging. This modality utilizes x-ray activated nanophosphors that luminesce when excited by ionizing photons. By doping phosphors with lanthanides, which emit light in the visible and near infrared range, the luminescence is suitable for biological applications. This study examines practical aspects of this new modality including phosphor concentration, light emission linearity, detector damage, and spectral emission characteristics. Finally, the contrast produced by these phosphors is compared to that of x-ray fluoroscopy.Gadolinium and lanthanum oxysulfide phosphors doped with terbium (green emission) or europium (red emission) were studied. The light emission was imaged in a clinical x-ray scanner with a cooled CCD camera and a spectrophotometer; dose measurements were determined with a calibrated dosimeter. Using these properties, in addition to luminescence efficiency values found in the literature for a similar phosphor, minimum concentration calculations are performed. Finally, a 2.5 cm agar phantom with a 1 cm diameter cylindrical phosphor-filled inclusion (diluted at 10 mg/ml) is imaged to compare x-ray luminescence contrast with x-ray fluoroscopic contrast at a superficial location.Dose to the CCD camera in the chosen imaging geometry was measured at less than 0.02 cGy/s. Emitted light was found to be linear with dose (R(2)= 1) and concentration (R(2)= 1). Emission peaks for clinical x-ray energies are less than 3 nm full width at half maximum, as expected from lanthanide dopants. The minimum practical concentration necessary to detect luminescent phosphors is dependent on dose; it is estimated that subpicomolar concentrations are detectable at the surface of the tissue with typical mammographic doses, with the minimum detectable concentration increasing with depth and decreasing with dose. In a reflection geometry, x-ray luminescence had nearly a 430-fold greater contrast to background than x-ray fluoroscopy.X-ray luminescence has the potential to be a promising new modality for enabling molecular imaging within x-ray scanners. Although much work needs to be done to ensure biocompatibility of x-ray exciting phosphors, the benefits of this modality, highlighted in this work, encourage further study.

Abstract

Realizing the full potential of high-resolution positron emission tomography (PET) systems involves accurately positioning events in which the annihilation photon deposits all its energy across multiple detector elements. Reconstructing the complete sequence of interactions of each photon provides a reliable way to select the earliest interaction because it ensures that all the interactions are consistent with one another. Bayesian estimation forms a natural framework to maximize the consistency of the sequence with the measurements while taking into account the physics of gamma-ray transport. An inherently statistical method, it accounts for the uncertainty in the measured energy and position of each interaction. An algorithm based on maximum a posteriori (MAP) was evaluated for computer simulations. For a high-resolution PET system based on cadmium zinc telluride detectors, 93.8% of the recorded coincidences involved at least one photon multiple-interactions event (PMIE). The MAP estimate of the first interaction was accurate for 85.2% of the single photons. This represents a two-fold reduction in the number of mispositioned events compared to minimum pair distance, a simpler yet efficient positioning method. The point-spread function of the system presented lower tails and higher peak value when MAP was used. This translated into improved image quality, which we quantified by studying contrast and spatial resolution gains.

Abstract

List-mode processing provides an efficient way to deal with sparse projections in iterative image reconstruction for emission tomography. An issue often reported is the tremendous amount of computation required by such algorithm. Each recorded event requires several back- and forward line projections. We investigated the use of the programmable graphics processing unit (GPU) to accelerate the line-projection operations and implement fully-3D list-mode ordered-subsets expectation-maximization for positron emission tomography (PET). We designed a reconstruction approach that incorporates resolution kernels, which model the spatially-varying physical processes associated with photon emission, transport and detection. Our development is particularly suitable for applications where the projection data is sparse, such as high-resolution, dynamic, and time-of-flight PET reconstruction. The GPU approach runs more than 50 times faster than an equivalent CPU implementation while image quality and accuracy are virtually identical. This paper describes in details how the GPU can be used to accelerate the line projection operations, even when the lines-of-response have arbitrary endpoint locations and shift-varying resolution kernels are used. A quantitative evaluation is included to validate the correctness of this new approach.